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New Languages Vs. Old For Parallel Programming
joabj writes "Getting the most from multicore processors is becoming an increasingly difficult task for programmers. DARPA has commissioned a number of new programming languages, notably X10 and Chapel, written especially for developing programs that can be run across multiple processors, though others see them as too much of a departure to ever gain widespread usage among coders."
True enough, but the class of applications for which parallel processing is useful is growing rapidly as programmers learn to think in those terms. Any program with a "for" or "while" loop in which the results of one iteration do not depend on the results of the previous iteration, as well as a fair number of such loops in which the results do have such a dependency, is a candidate for parallelization -- and that means most of the programs which most programmers will ever write. We just need the languages not to make coding this way too painful.
The correlation between ignorance of statistics and using "correlation is not causation" as an argument is close to 1.
Check out Clojure. The only programming language around that really addresses the issue of programming in a multi-core environment. It's also quite a sweet language besides that.
I've been very disappointed in parallel programming support. The C/C++ community has a major blind spot in this area - they think parallelism is an operating system feature, not a language issue. As a result, C and C++ provide no assistance in keeping track of what locks what. Hence race conditions. In Java, the problem was at least thought about, but "synchronized" didn't work out as well as expected. Microsoft Research people have done some good work in this area, and some of it made it into C#, but they have too much legacy to deal with.
At the OS level, in most operating systems, the message passing primitives suck. The usual approach in the UNIX/Linux world is to put marshalling on top of byte streams on top of sockets. Stuff like XML and CORBA, with huge overhead. The situation sucks so bad that people think JSON is a step forward.
What you usually want is a subroutine call; what the OS usually gives you is an I/O operation. There are better and faster message passing primitives (see MsgSend/MsgReceive in QNX), but they've never achieved any traction in the UNIX/Linux world. Nobody uses System V IPC, a mediocre idea from the 1980s. For that matter, there are still applications being written using lock files.
Erlang is one of the few parallel languages actually used to implement large industrial applications.
Whoever told you that is mistaken.
The easiest way to take advantage of a multiprocessing environment is to use techniques that will be familiar to any high level programmer. For example, you don't write for loops, you call functions written in a low level language to do things like that for you. Those low level functions can be easily parallelized, giving all your code a boost.